Deborah Smith Pegues, especializa en comportamiento y autora de éxitos de ventas como Controla tu lengua en 30 días (más de 500.000 ejemplares vendidos), arroja luz sobre los miedos racionales e irracionales y ofrece a los lectores un camino de esperanza y seguridad. Con la claridad y la sabiduría práctica que le caracterizan, Deborah Smith Pegues te ofrece esperanza y seguridad a la hora de tratar los temores relativos a las relaciones, la salud, la seguridad, las finanzas y las emociones con unos principios bíblicos y una ayuda práctica. En cada paso del proceso, te da poder sobre el miedo ayudándote a entender -la raíz de tus temores -la perspectiva de Dios sobre tus ansiedades, miedos y fobias -cómo responder a los desencadenantes del temor siendo consciente de ellos y teniendo confianza en ti -las maneras de asumir los temores saludables y resistirte a los que no lo son -cómo neutralizar tus temores puede potenciar al máximo tu vida Si te encuentras caminando por un campo plagado con las minas de tus constantes temores, este libro te ayudará a convertir el temor en esa clase de paz que sobrepasa todo entendimiento.
This book comprises the lectures of a two-semester course on quantum field theory, presented in a quite informal and personal manner. The course starts with relativistic one-particle systems, and develops the basics of quantum field theory with an analysis on the representations of the Poincaré group. Canonical quantization is carried out for scalar, fermion, Abelian and non-Abelian gauge theories. Covariant quantization of gauge theories is also carried out with a detailed description of the BRST symmetry. The Higgs phenomenon and the standard model of electroweak interactions are also developed systematically. Regularization and (BPHZ) renormalization of field theories as well as gauge theories are discussed in detail, leading to a derivation of the renormalization group equation. In addition, two chapters — one on the Dirac quantization of constrained systems and another on discrete symmetries — are included for completeness, although these are not covered in the two-semester course.This second edition includes two new chapters, one on Nielsen identities and the other on basics of global supersymmetry. It also includes two appendices, one on fermions in arbitrary dimensions and the other on gauge invariant potentials and the Fock-Schwinger gauge.
“There are moments when a story shakes you...Barely Missing Everything is one of those stories, and Mendez, a gifted storyteller with a distinct voice, is sure to bring a quake to the literary landscape.” —Jason Reynolds, New York Times bestselling author of Long Way Down In the tradition of Jason Reynolds and Matt de la Peña, this heartbreaking, no-holds-barred debut novel told from three points of view explores how difficult it is to make it in life when you—your life, brown lives—don’t matter. Juan has plans. He’s going to get out of El Paso, Texas, on a basketball scholarship and make something of himself—or at least find something better than his mom Fabi’s cruddy apartment, her string of loser boyfriends, and a dead dad. Basketball is going to be his ticket out, his ticket up. He just needs to make it happen. His best friend JD has plans, too. He’s going to be a filmmaker one day, like Quentin Tarantino or Guillermo del Toro (NOT Steven Spielberg). He’s got a camera and he’s got passion—what else could he need? Fabi doesn’t have a plan anymore. When you get pregnant at sixteen and have been stuck bartending to make ends meet for the past seventeen years, you realize plans don’t always pan out, and that there are some things you just can’t plan for… Like Juan’s run-in with the police, like a sprained ankle, and a tanking math grade that will likely ruin his chance at a scholarship. Like JD causing the implosion of his family. Like letters from a man named Mando on death row. Like finding out this man could be the father your mother said was dead. Soon Juan and JD are embarking on a Thelma and Louise—like road trip to visit Mando. Juan will finally meet his dad, JD has a perfect subject for his documentary, and Fabi is desperate to stop them. But, as we already know, there are some things you just can’t plan for…
For a two-semester or a three-quarter calculus-based Introduction to the Mathematics of Statistics course. This classic, calculus-based introduction to the theory - and application - of statistics provides an unusually comprehensive depth and breadth of coverage and reflects the state-of-the-art in statistical thinking, the teaching of statistics, and current practices - including the use of the computer. *NEW - Places greater emphasis on the use of computers in performing statistical calculations. *NEW - Includes new exercises - many of which require the use of a computer. *NEW - Expands coverage of Analysis of Variance to include the two-way analysis-of-variance model with interaction and a discussion of multiple comparisons. *NEW - Adds appendices which summarize the properties of the special probability distributions and density functions that appear in the text. *Places greater emphasis on the use of computers in performing statistical calculations. *Comprehensive coverage of statistical theories. *Features more than 1,100 problems and exercises - divided into theory and applications.
Master Bayesian Inference through Practical Examples and Computation–Without Advanced Mathematical Analysis Bayesian methods of inference are deeply natural and extremely powerful. However, most discussions of Bayesian inference rely on intensely complex mathematical analyses and artificial examples, making it inaccessible to anyone without a strong mathematical background. Now, though, Cameron Davidson-Pilon introduces Bayesian inference from a computational perspective, bridging theory to practice–freeing you to get results using computing power. Bayesian Methods for Hackers illuminates Bayesian inference through probabilistic programming with the powerful PyMC language and the closely related Python tools NumPy, SciPy, and Matplotlib. Using this approach, you can reach effective solutions in small increments, without extensive mathematical intervention. Davidson-Pilon begins by introducing the concepts underlying Bayesian inference, comparing it with other techniques and guiding you through building and training your first Bayesian model. Next, he introduces PyMC through a series of detailed examples and intuitive explanations that have been refined after extensive user feedback. You’ll learn how to use the Markov Chain Monte Carlo algorithm, choose appropriate sample sizes and priors, work with loss functions, and apply Bayesian inference in domains ranging from finance to marketing. Once you’ve mastered these techniques, you’ll constantly turn to this guide for the working PyMC code you need to jumpstart future projects. Coverage includes • Learning the Bayesian “state of mind” and its practical implications • Understanding how computers perform Bayesian inference • Using the PyMC Python library to program Bayesian analyses • Building and debugging models with PyMC • Testing your model’s “goodness of fit” • Opening the “black box” of the Markov Chain Monte Carlo algorithm to see how and why it works • Leveraging the power of the “Law of Large Numbers” • Mastering key concepts, such as clustering, convergence, autocorrelation, and thinning • Using loss functions to measure an estimate’s weaknesses based on your goals and desired outcomes • Selecting appropriate priors and understanding how their influence changes with dataset size • Overcoming the “exploration versus exploitation” dilemma: deciding when “pretty good” is good enough • Using Bayesian inference to improve A/B testing • Solving data science problems when only small amounts of data are available Cameron Davidson-Pilon has worked in many areas of applied mathematics, from the evolutionary dynamics of genes and diseases to stochastic modeling of financial prices. His contributions to the open source community include lifelines, an implementation of survival analysis in Python. Educated at the University of Waterloo and at the Independent University of Moscow, he currently works with the online commerce leader Shopify.
Statistics has evolved into an exciting discipline which uses deep theory and powerful software to shed light on the world around us: from clinical trials in medicine, to economics, sociology, and countless other subjects vital to understanding modern life. This Very Short Introduction explores and explains how statistics works today.
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
Oli: para oligo, en cada niveles algunas opciones de palabras claves, sobre algunos niveles Cogno: para conocimiento, articulacion de conceptos claves, para integrar democraticamente y en grupos operativos Grafia: para une dibujo de grafos geometricamente logicos. En total, un marco logico para caracterizar situaciones teoricas y aplicadas. Por le tanto una metodologia, aplicada para aprender en estructurar marcos logicos integros. 50 ejemplos de aplicacion en muchos registros de ciencias desde la filosofia hasta las ciencias sociales; epistemologias cuya filosofia de diseño se presta al manejo democratico de programas compartidos.
